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After that, Section 5 explains the mapping of RMRS structures into OWL descriptions.
Finally, Section 6 shows that a subsequent description logic reasoner can utilize these descriptions to infer new knowledge.
2 The relationship between description and feature logics
Description logics (DL) (Baader et al., 2003) and feature logics (FL) (Carpenter, 1992) have been pursued independently for quite a while. Their close relationship was recognized by (Nebel and Smolka, 1990).
Instances of both families of knowledge representation formalisms are usually decidable two-variable fragments of first-order predicate logic.
Even though DL dialects usually have an intractable worst-case complexity, average-case reasoning is usually fast, due to the availability of highly-optimized tableaux reasoners.
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After that, Section 5 explains the mapping of RMRS structures into OWL descriptions.
Finally, Section 6 shows that a subsequent description logic reasoner can utilize these descriptions to infer new knowledge.
2 The relationship between description and feature logics
Description logics (DL) (Baader et al., 2003) and feature logics (FL) (Carpenter, 1992) have been pursued independently for quite a while. Their close relationship was recognized by (Nebel and Smolka, 1990).
Instances of both families of knowledge representation formalisms are usually decidable two-variable fragments of first-order predicate logic.
Even though DL dialects usually have an intractable worst-case complexity, average-case reasoning is usually fast, due to the availability of highly-optimized tableaux reasoners.
...".

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Analogous mappings are supported for other grammars available in the DELPH-IN repository (see http://www.delph-in.net).
The mapping basically transports the surface string, a character span, and a generic lexicon type of the deep grammar for a chart item to be generated in an XML format, readable by the deep parser.
A sample output of the semantic representation generated by the deep parser is shown in Figure 1.
The semantic representation format, called RMRS, is described in (Copestake, 2003) and in Section 5.3 below. In addition to the basic named entity type mapping for default lexicon entries, the recognized concepts are also useful for constraining the semantic sort in the deep grammar in a more fine-grained way (e.g., for disambiguation).
The deep parser's XML input chart format foresees "injection" of such types into deep structures.
Here, objid and other structured information, like given name and surname, can be preserved in the representation.
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